This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Abad, P., Benito, S., & Lopez, C. (2013). A comprehensive review of value at risk methodologies. The Spanish Review of Financial Economics, 12(1), 15–32.AbadP.BenitoS.LopezC.2013A comprehensive review of value at risk methodologies121153210.1016/j.srfe.2013.06.001Search in Google Scholar
Allen, D., Singh, A., & Powell, R. (2011). Value at Risk estimation using extreme value theory. ECU Publications. Retrieved from http://ro.ecu.edu.au/ecuworks2011/.AllenD.SinghA.PowellR.2011Value at Risk estimation using extreme value theoryRetrieved from http://ro.ecu.edu.au/ecuworks2011/.Search in Google Scholar
Alves, M., & Santos, P. (2013). Conditional EVT for VAR estimation: comparison with a new independence test. In J. Lita da Silva (Ed.), Advances in regression, survival analysis, extreme values, Markov processes and other statistical applications (pp. 183–191). Berlin, Germany: Springer.AlvesM.SantosP.2013Conditional EVT for VAR estimation: comparison with a new independence testInLita da SilvaJ.(Ed.),183191Berlin, GermanySpringer10.1007/978-3-642-34904-1_19Search in Google Scholar
Angelidis, T., Benos, A., & Degiannakis, S. (2007). A robust VAR model under different time periods and weighting schemes. Review of Quantitative Finance and Accounting, 28, 187–201.AngelidisT.BenosA.DegiannakisS.2007A robust VAR model under different time periods and weighting schemes2818720110.1007/s11156-006-0010-ySearch in Google Scholar
Artzner, P., Eber, J.-M., & Heath, D. (1999). Coherent measures of risk. Mathematical Finance, 9, 203–228.ArtznerP.EberJ.-M.HeathD.1999Coherent measures of risk920322810.1017/CBO9780511615337.007Search in Google Scholar
Balkema, A., & de Haan, L. (1974). Residual lifetime at great age. Annals of Probability, 2, 792–804.BalkemaA.de HaanL.1974Residual lifetime at great age279280410.1214/aop/1176996548Search in Google Scholar
Bao, Y., Lee, T.-H., & Saltoglu, B. (2006). Evaluating predictive performance of Value-at-Risk models in emerging markets: a reality check. Journal of Forecasting, 25, 101–128.BaoY.LeeT.-H.SaltogluB.2006Evaluating predictive performance of Value-at-Risk models in emerging markets: a reality check2510112810.1002/for.977Search in Google Scholar
BCBS. (1996). Supervisory framework for the use of ‘backtesting’ in conjuction with the internal models approach to market risk capital requirements. Basel: Basel Committee on Banking Supervision. Retrieved from https://www.bis.org/publ/bcbs22.htm.BCBS1996BaselBasel Committee on Banking SupervisionRetrieved from https://www.bis.org/publ/bcbs22.htm.Search in Google Scholar
Bee, M., & Miorelli, F. (2010). Dynamic VaR models and the peaks over threshold method for market risk measurement: an empirical investigation during a financial crisis. Department of Economics Working Papers 1009, Department of Economics, University of Trento, Italia.BeeM.MiorelliF.2010Department of Economics Working Papers 1009,Department of Economics, University of TrentoItaliaSearch in Google Scholar
Bhattacharyya, M., & Ritolia, G. (2008). Conditional VaR using EVT – towards a planned margin scheme. International Review of Financial Analysis, 17, 382–395.BhattacharyyaM.RitoliaG.2008Conditional VaR using EVT – towards a planned margin scheme1738239510.1016/j.irfa.2006.08.004Search in Google Scholar
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, 307–327.BollerslevT.1986Generalized autoregressive conditional heteroskedasticity3130732710.1016/0304-4076(86)90063-1Search in Google Scholar
Bollerslev, T., Todorov, V., & Li, S. (2013). Jump tails, extreme dependencies, and the distribution of stock returns. Journal of Econometrics, 172(2), 307–324.BollerslevT.TodorovV.LiS.2013Jump tails, extreme dependencies, and the distribution of stock returns172230732410.1016/j.jeconom.2012.08.014Search in Google Scholar
Bommier, E. (2014). Peaks-over-threshold modelling of environmental data. Retrieved from https://uu.diva-portal.org/smash/get/diva2:760802/FULLTEXT01.pdf.BommierE.2014Retrieved from https://uu.diva-portal.org/smash/get/diva2:760802/FULLTEXT01.pdf.Search in Google Scholar
Bystrom, H. (2001). Managing risks in tranquil and volatile markets using conditional extreme value theory. International Review of Financial Analysis, 13(2), 133–152.BystromH.2001Managing risks in tranquil and volatile markets using conditional extreme value theory13213315210.1016/j.irfa.2004.02.003Search in Google Scholar
Caires, S. (2009). A comparative simulation study of the annual Maxima and the peaks-over-threshold methods. “Hydraulic Engineering Reports” (Deltares Report 1200264-002). Retrieved from https://repository.tudelft.nl/islandora/object/uuid:143b0f1e-f61e-44ab-8da3-9241970d915b?collection=research.CairesS.2009“Hydraulic Engineering Reports” (Deltares Report 1200264-002). Retrieved from https://repository.tudelft.nl/islandora/object/uuid:143b0f1e-f61e-44ab-8da3-9241970d915b?collection=research.Search in Google Scholar
Caporin, M. (2008). Evaluating Value-at-Risk measures in the presence of long memory conditional volatility. Journal of Risk, 10, 79–110.CaporinM.2008Evaluating Value-at-Risk measures in the presence of long memory conditional volatility107911010.21314/JOR.2008.172Search in Google Scholar
Chlebus, M. (2014). Market risk measuring using value at risk – two-step approach (PhD thesis), Faculty of Economic Sciences, University of Warsaw.ChlebusM.2014(PhD thesis),Faculty of Economic Sciences, University of WarsawSearch in Google Scholar
Christoffersen, P. (1998). Evaluating interval forecasting. International Economic Review, 39, 841–862.ChristoffersenP.1998Evaluating interval forecasting3984186210.2307/2527341Search in Google Scholar
Darbha, G. (2001). Value-at-Risk for fixed income portfolios – a comparison of alter-native models. Mumbai: National Stock Exchange. Retrieved from https://www.researchgate.net/publication/228607410_Value-at-Risk_for_Fixed_Income_portfolios-A_comparison_of_alternative_models.DarbhaG.2001MumbaiNational Stock ExchangeRetrieved from https://www.researchgate.net/publication/228607410_Value-at-Risk_for_Fixed_Income_portfolios-A_comparison_of_alternative_models.Search in Google Scholar
Da Silva, A., & de Melo Mendes, B. V. (2003). Value-at-Risk and extreme returns in Asian stock markets. International Journal of Business, 8(1), 24.Da SilvaA.de Melo MendesB. V.2003Value-at-Risk and extreme returns in Asian stock markets8124Search in Google Scholar
Embrechts, P., Kluppelberg, C., & Mikosch, T. (1997). Modelling extremal events for Insurance and Finance. Springer-Verlag, 295–305.EmbrechtsP.KluppelbergC.MikoschT.1997Springer-Verlag29530510.1007/978-3-642-33483-2Search in Google Scholar
Engle, R. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50, 987–1007.EngleR.1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation50987100710.2307/1912773Search in Google Scholar
Engle, R., & Patton, A. (2001). What good is a volatility model? Quantitative Finance, Vol. 1, 237–245.EngleR.PattonA.2001What good is a volatility model?123724510.1016/B978-075066942-9.50004-2Search in Google Scholar
Engle, R. F., & Manganelli, S. (2004). CAViaR: conditional autoregressive value at risk by regression quantiles. Journal of Business & Economic Statistics, 22(4), 367–381.EngleR. F.ManganelliS.2004CAViaR: conditional autoregressive value at risk by regression quantiles22436738110.1198/073500104000000370Search in Google Scholar
Ergun, T., & Jun, J. (2010). Time-varying higher-order conditional moments and forecasting intraday VaR and expected shortfall. The Quarterly Review of Economics and Finance, 50, 264–272.ErgunT.JunJ.2010Time-varying higher-order conditional moments and forecasting intraday VaR and expected shortfall5026427210.1016/j.qref.2010.03.003Search in Google Scholar
Fisher, R., & Tippett, L. (1928). Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proceedings of the Cambridge Philosophical Society, 180–190.FisherR.TippettL.1928Limiting forms of the frequency distribution of the largest or smallest member of a sample18019010.1017/S0305004100015681Search in Google Scholar
Flugentiusson, H. (2012). Push it to the limit. Testing the usefulness of extreme value theory in electricity markets. Lund University Publications. Retrieved from http://lup.lub.lu.se/luur/download?-func=downloadFile&recordOId=3166413&file-OId=3166414.FlugentiussonH.2012Lund University PublicationsRetrieved from http://lup.lub.lu.se/luur/download?-func=downloadFile&recordOId=3166413&file-OId=3166414.Search in Google Scholar
Gencay, R., & Selcuk, F. (2004). Extreme value theory and Value-at-Risk: Relative performance in emerging markets. International Journal of Forecasting, 20, 287–303.GencayR.SelcukF.2004Extreme value theory and Value-at-Risk: Relative performance in emerging markets2028730310.1016/j.ijforecast.2003.09.005Search in Google Scholar
Gencay, R., Selcuk, F., & Ulugulyagci, A. (2003). High volatility, thick tails and extreme value theory in Value-at-Risk estimation. Insurance: Mathematics and Economics, 33, 337–356.GencayR.SelcukF.UlugulyagciA.2003High volatility, thick tails and extreme value theory in Value-at-Risk estimation3333735610.1016/j.insmatheco.2003.07.004Search in Google Scholar
Kourouma, L., Dupre, D., Sanfilippo, G., & Taramasco, O. (2010). Extreme value at risk and expected shortfall during financial crisis. Retrieved from https://ssrn.com/abstract=1744091;doi:10.2139/ssrn.1744091.KouroumaL.DupreD.SanfilippoG.TaramascoO.2010Retrieved from https://ssrn.com/abstract=1744091;10.2139/ssrn.1744091Open DOISearch in Google Scholar
Kupiec, P. (1995). Techniques for verifying the accuracy of risk measurement models, Journal of Derivatives, 3(2), 73–84.KupiecP.1995Techniques for verifying the accuracy of risk measurement models32738410.3905/jod.1995.407942Search in Google Scholar
Lopez, J. (1999). Methods for evaluating Value-at-Risk estimates. Federal Reserve Bank of San Francisco Economic Review, 2, 3–17.LopezJ.1999Methods for evaluating Value-at-Risk estimates231710.2139/ssrn.1029673Search in Google Scholar
Manganelli, S., & Engle, R. (2001). Value at Risk Models in Finance. ECB Working Paper No. 75, available at SSRN: https://ssrn.com/abstract=356220ManganelliS.EngleR.2001ECB Working Paper No. 75, available at SSRN: https://ssrn.com/abstract=35622010.2139/ssrn.356220Search in Google Scholar
Marimoutou, V., Raggad, B., & Trabelsi, A. (2009). Extreme value theory and value at risk: application to oil market. Energy Economics, 31, 519–530.MarimoutouV.RaggadB.TrabelsiA.2009Extreme value theory and value at risk: application to oil market3151953010.1016/j.eneco.2009.02.005Search in Google Scholar
Marinelli C., d’Addona S., & Rachev T. (2007). A comparison of some univariate models for Value-at-Risk and expected shortfall. International Journal of Theoretical and Applied Finance, 10(06), 1043–1075.MarinelliC.d’AddonaS.RachevT.2007A comparison of some univariate models for Value-at-Risk and expected shortfall10061043107510.1142/S0219024907004548Search in Google Scholar
Mutu, S., Balogh, P., & Moldovan, D. (2011). The efficiency of value at risk models on central and eastern European stock markets. International Journal of Mathematics and Computers in Simulation, 5, 110–117.MutuS.BaloghP.MoldovanD.2011The efficiency of value at risk models on central and eastern European stock markets5110117Search in Google Scholar
Nozari, M., Raei, S., Jahanguin, P., & Bahramgiri, M. (2010). A comparison of heavy-tailed estimates and filtered historical simulation: evidence from emerging markets. International Review of Business Papers, 6(4), 347–359.NozariM.RaeiS.JahanguinP.BahramgiriM.2010A comparison of heavy-tailed estimates and filtered historical simulation: evidence from emerging markets64347359Search in Google Scholar
Pagan, A. (1996). The econometrics of financial markets. Journal of Empirical Finance, 3, 15–102.PaganA.1996The econometrics of financial markets31510210.1016/0927-5398(95)00020-8Search in Google Scholar
Pickands, J. (1975). Statistical inference using extreme order statistics. Annals of Statistics, 3, 119–131.PickandsJ.1975Statistical inference using extreme order statistics311913110.1214/aos/1176343003Search in Google Scholar